Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

Growth rates

Heat maps

  • The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
  • The first plot compares growth rate for total cases; the second, growth rate for total deaths.
  • The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
  • The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
    • You can use the plots to track each geography over time and to compare the geographies to one another.
    • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

  • This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
    • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
  • Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
  • Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
    • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
    • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

  • This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
    • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
  • Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
  • Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
    • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
    • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

  • This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
  • For each metric, in addition to the tables, the trends for the top states are plotted over time.
    • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)
Ranking State Cases Per Million
1 North Dakota 127,078
2 South Dakota 121,117
3 Utah 104,931
4 Rhode Island 103,586
5 Tennessee 101,678
6 Wisconsin 99,851
7 Arizona 99,272
8 Iowa 99,249
9 Nebraska 96,880
10 Oklahoma 94,286
11 Arkansas 94,130
12 Kansas 92,544
13 Indiana 91,221
14 Alabama 89,976
15 Idaho 89,297
16 Mississippi 88,778
17 Nevada 87,991
18 Wyoming 87,943
19 Illinois 87,138
20 Montana 85,763
21 Louisiana 82,572
22 South Carolina 81,248
23 New Mexico 80,695
24 Minnesota 80,689
25 California 80,623
26 Georgia 79,378
27 Missouri 78,529
28 Kentucky 78,160
29 Texas 77,595
30 Florida 76,797
31 Delaware 76,584
32 New Jersey 74,622
33 Ohio 73,942
34 Massachusetts 72,547
35 Alaska 72,424
36 North Carolina 68,704
37 New York 68,673
38 Colorado 67,368
39 Connecticut 66,702
40 West Virginia 64,340
41 Pennsylvania 63,189
42 Michigan 59,613
43 Maryland 56,514
44 Virginia 55,350
45 District of Columbia 50,019
46 New Hampshire 45,845
47 Washington 39,990
48 Puerto Rico 39,027
49 Oregon 32,758
50 Maine 27,226
51 Hawaii 17,722
52 Vermont 17,681

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)
Ranking State New Cases Per Million
1 South Carolina 895
2 Arizona 885
3 Oklahoma 846
4 New York 719
5 Delaware 702
6 Georgia 699
7 North Carolina 675
8 Massachusetts 670
9 New Jersey 623
10 Utah 617
11 California 589
12 Alabama 586
13 Kentucky 585
14 Mississippi 571
15 Florida 551
16 Arkansas 535
17 Virginia 501
18 New Hampshire 500
19 West Virginia 500
20 Nevada 473
21 Texas 459
22 Tennessee 456
23 Indiana 451
24 Ohio 416
25 Illinois 399
26 Louisiana 397
27 Maryland 382
28 New Mexico 378
29 Pennsylvania 372
30 Kansas 348
31 District of Columbia 325
32 Wisconsin 325
33 Alaska 318
34 Missouri 310
35 Nebraska 301
36 Rhode Island 298
37 Colorado 291
38 Montana 286
39 Iowa 285
40 South Dakota 281
41 Wyoming 272
42 Minnesota 249
43 Vermont 241
44 Puerto Rico 240
45 Maine 238
46 Idaho 220
47 North Dakota 196
48 Connecticut 188
49 Washington 179
50 Oregon 173
51 Michigan 138
52 Hawaii 101

Total deaths

Table of total deaths per million residents (all 50 states)
Ranking State Deaths Per Million
1 New Jersey 2,358
2 New York 2,153
3 Massachusetts 2,050
4 Rhode Island 1,966
5 Mississippi 1,939
6 South Dakota 1,927
7 Connecticut 1,912
8 North Dakota 1,884
9 Louisiana 1,842
10 Arizona 1,681
11 Illinois 1,631
12 Pennsylvania 1,609
13 Arkansas 1,526
14 Michigan 1,518
15 New Mexico 1,500
16 Indiana 1,443
17 Iowa 1,422
18 Alabama 1,358
19 Nevada 1,307
20 Tennessee 1,285
21 South Carolina 1,271
22 District of Columbia 1,235
23 Kansas 1,235
24 Georgia 1,209
25 Texas 1,208
26 Florida 1,177
27 Maryland 1,135
28 Missouri 1,133
29 Minnesota 1,092
30 Montana 1,077
31 Delaware 1,069
32 Wisconsin 1,063
33 West Virginia 1,057
34 Nebraska 1,010
35 Wyoming 986
36 Colorado 970
37 California 939
38 Idaho 935
39 Ohio 916
40 North Carolina 833
41 Oklahoma 828
42 Kentucky 825
43 New Hampshire 725
44 Virginia 712
45 Puerto Rico 555
46 Washington 549
47 Utah 497
48 Oregon 446
49 Maine 404
50 Alaska 341
51 Vermont 272
52 Hawaii 239

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)
Ranking State New Deaths Per Million
1 Alabama 19
2 Arizona 19
3 New Mexico 16
4 Montana 15
5 Arkansas 12
6 Nevada 12
7 Pennsylvania 12
8 South Dakota 12
9 Wyoming 12
10 California 11
11 Georgia 11
12 Mississippi 11
13 Oklahoma 11
14 South Carolina 11
15 Texas 11
16 Massachusetts 10
17 North Carolina 10
18 New York 9
19 Florida 8
20 Louisiana 8
21 Michigan 8
22 Tennessee 8
23 West Virginia 8
24 Kentucky 7
25 Maryland 7
26 New Jersey 7
27 Illinois 6
28 Indiana 6
29 New Hampshire 6
30 North Dakota 6
31 Ohio 5
32 Virginia 5
33 Wisconsin 5
34 Connecticut 4
35 Delaware 4
36 Iowa 4
37 Minnesota 4
38 Puerto Rico 4
39 Utah 4
40 Colorado 3
41 District of Columbia 3
42 Hawaii 3
43 Alaska 2
44 Idaho 2
45 Kansas 2
46 Missouri 2
47 Nebraska 2
48 Oregon 2
49 Rhode Island 2
50 Washington 2
51 Maine 1
52 Vermont 1

Counties

  • This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
    • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
  • In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
County State Cases Per Million Raw Ranking Percentile
Crowley Colorado 291,041 1 99
Dewey South Dakota 234,895 2 99
Bent Colorado 230,052 3 99
Lincoln Arkansas 230,037 4 99
Chattahoochee Georgia 227,652 5 99
Davidson Tennessee 117,499 266 91
Richland South Carolina 81,694 1415 54
York South Carolina 74,643 1777 43
Orange California 74,413 1786 43
Pierce Washington 37,273 2888 8

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
County State Deaths Per Million Raw Ranking Percentile
Gove Kansas 8,346 1 99
Jerauld South Dakota 7,948 2 99
Dickey North Dakota 6,568 3 99
Gregory South Dakota 6,452 4 99
Grant Nebraska 6,421 5 99
Davidson Tennessee 998 1897 39
Richland South Carolina 948 1973 37
Orange California 831 2147 31
York South Carolina 754 2261 28
Pierce Washington 488 2642 15

Our county percentiles over time

Raw counts

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons